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To foster research on dialog policy learning for virtual digital assistants, several task-oriented dialog corpora have been introduced in recent years, such as SimDial [1]}, MultiWoZ [2]}, Taskmaster [3]}, and Schema Guided Dialog [4]}, to name a few.
Deep learning approaches, including mixture models [5]} hierarchical encoder/decoder [6]}, [7]}, reinforcement learning [8]}, and pre-trained language models [9]}, [10]}, [11]}, have significantly advanced dialog policy research in the past few years [12]}, setting new state-of-the-art performance limits.
